Staff Applied Scientist- Embodied AI via Smarter Data

London

Full-time

Job Description

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The role

Science is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

Where you’ll have impact:

We’re building AI-native driving intelligence—from raw sensor input to on-road decisions—with a foundation model approach at the core. As part of this, we’re looking for an applied scientist who can help shape how we learn from data: not just more of it, but smarter use of it.

This role sits at the intersection of data curation, model evaluation, interpretability, and scientific data optimization. You’ll work closely with our world-class behavior modeling and architecture teams to make the data layer a first-class citizen—turning fleet-scale data into structured, targeted learning signals.

This is a unique chance to join a science-first team working at the cutting edge of end-to-end autonomy, where model behavior, interpretability, and generalization all hinge on the right data.

Key responsibilities:

Design principled data selection and sampling strategies to improve model learning efficiency and generalization.
Identify and prioritize high-leverage data slices using signals such as loss, uncertainty, rarity, or alignment with specific driving behaviors.
Design rigorous offline and on-road evaluation protocols to measure the impact of experimentation on performance.
Investigate the interplay between data composition and model behavior, aiming to uncover how different training distributions shape learned representations and decision-making.
Understanding and design of how the chosen data affects model behaviour in different scenarios

About you

In order to set you up for success as an Applied Scientist at Wayve, we’re looking for the following skills and experience.

Essential

Proven experience in curating, selecting, and maintaining datasets that directly improve performance of machine learning models.
5+ years of experience in ML engineering or applied research roles.
You have a deep understanding of the full lifecycle of ML research and deployment.
Deep knowledge of transformers for vision or language modelling.
You have strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools.
Enjoy thinking about data as a lever for model behavior, not just as input.
Understand the value of “fast signals” and quick feedback loops in ML iteration.

Desirable

Hands-on experience with large-scale data querying and wrangling, from writing SQL queries to designing custom selection criteria in Python/ML pipelines.
Publications in top ML conferences (e.g., NeurIPS, ICLR, ICML) or contributions to open-source ML tooling.
Experience with embeddings, representation learning, or token-level analysis.
Experience in AVs, robotics, simulation, or other embodied AI domains.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

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